Merge branch 'develop' into backtest_fitlivepredictions

This commit is contained in:
Wagner Costa Santos
2022-11-17 10:13:11 -03:00
51 changed files with 231 additions and 731 deletions

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@@ -108,7 +108,6 @@ def ask_user_config() -> Dict[str, Any]:
"binance",
"binanceus",
"bittrex",
"ftx",
"gateio",
"huobi",
"kraken",

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@@ -159,6 +159,7 @@ CONF_SCHEMA = {
'ignore_buying_expired_candle_after': {'type': 'number'},
'trading_mode': {'type': 'string', 'enum': TRADING_MODES},
'margin_mode': {'type': 'string', 'enum': MARGIN_MODES},
'reduce_df_footprint': {'type': 'boolean', 'default': False},
'liquidation_buffer': {'type': 'number', 'minimum': 0.0, 'maximum': 0.99},
'backtest_breakdown': {
'type': 'array',

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@@ -7,6 +7,7 @@ from datetime import datetime, timezone
from operator import itemgetter
from typing import Dict, List
import numpy as np
import pandas as pd
from pandas import DataFrame, to_datetime
@@ -313,3 +314,29 @@ def convert_ohlcv_format(
if erase and convert_from != convert_to:
logger.info(f"Deleting source data for {pair} / {timeframe}")
src.ohlcv_purge(pair=pair, timeframe=timeframe, candle_type=candle_type)
def reduce_dataframe_footprint(df: DataFrame) -> DataFrame:
"""
Ensure all values are float32 in the incoming dataframe.
:param df: Dataframe to be converted to float/int 32s
:return: Dataframe converted to float/int 32s
"""
logger.debug(f"Memory usage of dataframe is "
f"{df.memory_usage().sum() / 1024**2:.2f} MB")
df_dtypes = df.dtypes
for column, dtype in df_dtypes.items():
if column in ['open', 'high', 'low', 'close', 'volume']:
continue
if dtype == np.float64:
df_dtypes[column] = np.float32
elif dtype == np.int64:
df_dtypes[column] = np.int32
df = df.astype(df_dtypes)
logger.debug(f"Memory usage after optimization is: "
f"{df.memory_usage().sum() / 1024**2:.2f} MB")
return df

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@@ -392,7 +392,7 @@ class Edge:
# Returning a list of pairs in order of "expectancy"
return final
def _find_trades_for_stoploss_range(self, df, pair, stoploss_range):
def _find_trades_for_stoploss_range(self, df, pair: str, stoploss_range) -> list:
buy_column = df['enter_long'].values
sell_column = df['exit_long'].values
date_column = df['date'].values
@@ -407,7 +407,7 @@ class Edge:
return result
def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
ohlc_columns, stoploss, pair):
ohlc_columns, stoploss, pair: str):
"""
Iterate through ohlc_columns in order to find the next trade
Next trade opens from the first buy signal noticed to

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@@ -18,7 +18,6 @@ from freqtrade.exchange.exchange_utils import (amount_to_contract_precision, amo
timeframe_to_next_date, timeframe_to_prev_date,
timeframe_to_seconds, validate_exchange,
validate_exchanges)
from freqtrade.exchange.ftx import Ftx
from freqtrade.exchange.gateio import Gateio
from freqtrade.exchange.hitbtc import Hitbtc
from freqtrade.exchange.huobi import Huobi

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@@ -52,7 +52,6 @@ MAP_EXCHANGE_CHILDCLASS = {
SUPPORTED_EXCHANGES = [
'binance',
'bittrex',
'ftx',
'gateio',
'huobi',
'kraken',

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@@ -1,178 +0,0 @@
""" FTX exchange subclass """
import logging
from typing import Any, Dict, List, Optional, Tuple
import ccxt
from freqtrade.constants import BuySell
from freqtrade.enums import MarginMode, TradingMode
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
from freqtrade.exchange.common import API_FETCH_ORDER_RETRY_COUNT, retrier
from freqtrade.misc import safe_value_fallback2
logger = logging.getLogger(__name__)
class Ftx(Exchange):
_ft_has: Dict = {
"order_time_in_force": ['GTC', 'IOC', 'PO'],
"stoploss_on_exchange": True,
"ohlcv_candle_limit": 1500,
"ohlcv_require_since": True,
"ohlcv_volume_currency": "quote",
"mark_ohlcv_price": "index",
"mark_ohlcv_timeframe": "1h",
}
_supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
# TradingMode.SPOT always supported and not required in this list
# (TradingMode.MARGIN, MarginMode.CROSS),
# (TradingMode.FUTURES, MarginMode.CROSS)
]
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
return order['type'] == 'stop' and (
side == "sell" and stop_loss > float(order['price']) or
side == "buy" and stop_loss < float(order['price'])
)
@retrier(retries=0)
def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: BuySell, leverage: float) -> Dict:
"""
Creates a stoploss order.
depending on order_types.stoploss configuration, uses 'market' or limit order.
Limit orders are defined by having orderPrice set, otherwise a market order is used.
"""
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
if side == "sell":
limit_rate = stop_price * limit_price_pct
else:
limit_rate = stop_price * (2 - limit_price_pct)
ordertype = "stop"
stop_price = self.price_to_precision(pair, stop_price)
if self._config['dry_run']:
dry_order = self.create_dry_run_order(
pair, ordertype, side, amount, stop_price, leverage, stop_loss=True)
return dry_order
try:
params = self._params.copy()
if order_types.get('stoploss', 'market') == 'limit':
# set orderPrice to place limit order, otherwise it's a market order
params['orderPrice'] = limit_rate
if self.trading_mode == TradingMode.FUTURES:
params.update({'reduceOnly': True})
params['stopPrice'] = stop_price
amount = self.amount_to_precision(pair, amount)
self._lev_prep(pair, leverage, side)
order = self._api.create_order(symbol=pair, type=ordertype, side=side,
amount=amount, params=params)
self._log_exchange_response('create_stoploss_order', order)
logger.info('stoploss order added for %s. '
'stop price: %s.', pair, stop_price)
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return self.fetch_dry_run_order(order_id)
try:
orders = self._api.fetch_orders(pair, None, params={'type': 'stop'})
order = [order for order in orders if order['id'] == order_id]
self._log_exchange_response('fetch_stoploss_order', order)
if len(order) == 1:
if order[0].get('status') == 'closed':
# Trigger order was triggered ...
real_order_id: Optional[str] = order[0].get('info', {}).get('orderId')
# OrderId may be None for stoploss-market orders
# So we need to get it through the endpoint
# /conditional_orders/{conditional_order_id}/triggers
if not real_order_id:
res = self._api.privateGetConditionalOrdersConditionalOrderIdTriggers(
params={'conditional_order_id': order_id})
self._log_exchange_response('fetch_stoploss_order2', res)
real_order_id = res['result'][0]['orderId'] if res.get(
'result', []) else None
if real_order_id:
order1 = self._api.fetch_order(real_order_id, pair)
self._log_exchange_response('fetch_stoploss_order1', order1)
# Fake type to stop - as this was really a stop order.
order1['id_stop'] = order1['id']
order1['id'] = order_id
order1['type'] = 'stop'
order1['status_stop'] = 'triggered'
return order1
return order[0]
else:
raise InvalidOrderException(f"Could not get stoploss order for id {order_id}")
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Tried to get an invalid order (id: {order_id}). Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return {}
try:
order = self._api.cancel_order(order_id, pair, params={'type': 'stop'})
self._log_exchange_response('cancel_stoploss_order', order)
return order
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
if order['type'] == 'stop':
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']

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@@ -19,6 +19,7 @@ from sklearn.neighbors import NearestNeighbors
from freqtrade.configuration import TimeRange
from freqtrade.constants import Config
from freqtrade.data.converter import reduce_dataframe_footprint
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_seconds
from freqtrade.strategy.interface import IStrategy
@@ -1276,6 +1277,9 @@ class FreqaiDataKitchen:
dataframe = self.remove_special_chars_from_feature_names(dataframe)
if self.config.get('reduce_df_footprint', False):
dataframe = reduce_dataframe_footprint(dataframe)
return dataframe
def fit_labels(self) -> None:

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@@ -354,7 +354,7 @@ class FreqtradeBot(LoggingMixin):
if self.trading_mode == TradingMode.FUTURES:
self._schedule.run_pending()
def update_closed_trades_without_assigned_fees(self):
def update_closed_trades_without_assigned_fees(self) -> None:
"""
Update closed trades without close fees assigned.
Only acts when Orders are in the database, otherwise the last order-id is unknown.
@@ -379,7 +379,7 @@ class FreqtradeBot(LoggingMixin):
stoploss_order=order.ft_order_side == 'stoploss',
send_msg=False)
trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
trades = Trade.get_open_trades_without_assigned_fees()
for trade in trades:
if trade.is_open and not trade.fee_updated(trade.entry_side):
order = trade.select_order(trade.entry_side, False)

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@@ -35,9 +35,5 @@ def interest(
elif exchange_name == "kraken":
# Rounded based on https://kraken-fees-calculator.github.io/
return borrowed * rate * (one + FtPrecise(ceil(hours / four)))
elif exchange_name == "ftx":
# As Explained under #Interest rates section in
# https://help.ftx.com/hc/en-us/articles/360053007671-Spot-Margin-Trading-Explainer
return borrowed * rate * FtPrecise(ceil(hours)) / twenty_four
else:
raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")

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@@ -166,7 +166,7 @@ class Backtesting:
PairLocks.use_db = True
Trade.use_db = True
def init_backtest_detail(self):
def init_backtest_detail(self) -> None:
# Load detail timeframe if specified
self.timeframe_detail = str(self.config.get('timeframe_detail', ''))
if self.timeframe_detail:

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@@ -1,5 +1,5 @@
import logging
from typing import List
from typing import List, Optional
from sqlalchemy import inspect, select, text, tuple_, update
@@ -31,9 +31,9 @@ def get_backup_name(tabs: List[str], backup_prefix: str):
return table_back_name
def get_last_sequence_ids(engine, trade_back_name, order_back_name):
order_id: int = None
trade_id: int = None
def get_last_sequence_ids(engine, trade_back_name: str, order_back_name: str):
order_id: Optional[int] = None
trade_id: Optional[int] = None
if engine.name == 'postgresql':
with engine.begin() as connection:

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@@ -1144,7 +1144,8 @@ class Trade(_DECL_BASE, LocalTrade):
id = Column(Integer, primary_key=True)
orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan", lazy="joined")
orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan",
lazy="selectin", innerjoin=True)
exchange = Column(String(25), nullable=False)
pair = Column(String(25), nullable=False, index=True)

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@@ -84,11 +84,8 @@ async def _process_consumer_request(
# Limit the amount of candles per dataframe to 'limit' or 1500
limit = max(data.get('limit', 1500), 1500)
# They requested the full historical analyzed dataframes
analyzed_df = rpc._ws_request_analyzed_df(limit)
# For every dataframe, send as a separate message
for _, message in analyzed_df.items():
# For every pair in the generator, send a separate message
for message in rpc._ws_request_analyzed_df(limit):
response = WSAnalyzedDFMessage(data=message)
await channel_manager.send_direct(channel, response.dict(exclude_none=True))

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@@ -2,7 +2,7 @@ import asyncio
import logging
from ipaddress import IPv4Address
from threading import Thread
from typing import Any, Dict
from typing import Any, Dict, Optional
import orjson
import uvicorn
@@ -51,9 +51,9 @@ class ApiServer(RPCHandler):
# Exchange - only available in webserver mode.
_exchange = None
# websocket message queue stuff
_ws_channel_manager = None
_ws_channel_manager: ChannelManager
_ws_thread = None
_ws_loop = None
_ws_loop: Optional[asyncio.AbstractEventLoop] = None
def __new__(cls, *args, **kwargs):
"""
@@ -71,7 +71,7 @@ class ApiServer(RPCHandler):
return
self._standalone: bool = standalone
self._server = None
self._ws_queue = None
self._ws_queue: Optional[ThreadedQueue] = None
self._ws_background_task = None
ApiServer.__initialized = True
@@ -186,7 +186,7 @@ class ApiServer(RPCHandler):
self._ws_background_task = asyncio.run_coroutine_threadsafe(
self._broadcast_queue_data(), loop=self._ws_loop)
async def _broadcast_queue_data(self):
async def _broadcast_queue_data(self) -> None:
# Instantiate the queue in this coroutine so it's attached to our loop
self._ws_queue = ThreadedQueue()
async_queue = self._ws_queue.async_q
@@ -210,7 +210,8 @@ class ApiServer(RPCHandler):
finally:
# Disconnect channels and stop the loop on cancel
await self._ws_channel_manager.disconnect_all()
self._ws_loop.stop()
if self._ws_loop:
self._ws_loop.stop()
# Avoid adding more items to the queue if they aren't
# going to get broadcasted.
self._ws_queue = None

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@@ -35,8 +35,6 @@ class WebSocketChannel:
# The WebSocket object
self._websocket = WebSocketProxy(websocket)
# The Serializing class for the WebSocket object
self._serializer_cls = serializer_cls
self.drain_timeout = drain_timeout
self.throttle = throttle
@@ -50,7 +48,7 @@ class WebSocketChannel:
self._closed = asyncio.Event()
# Wrap the WebSocket in the Serializing class
self._wrapped_ws = self._serializer_cls(self._websocket)
self._wrapped_ws = serializer_cls(self._websocket)
def __repr__(self):
return f"WebSocketChannel({self.channel_id}, {self.remote_addr})"

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@@ -5,7 +5,7 @@ import logging
from abc import abstractmethod
from datetime import date, datetime, timedelta, timezone
from math import isnan
from typing import Any, Dict, List, Optional, Tuple, Union
from typing import Any, Dict, Generator, List, Optional, Tuple, Union
import arrow
import psutil
@@ -1063,23 +1063,20 @@ class RPC:
self,
pairlist: List[str],
limit: Optional[int]
) -> Dict[str, Any]:
) -> Generator[Dict[str, Any], None, None]:
""" Get the analysed dataframes of each pair in the pairlist """
timeframe = self._freqtrade.config['timeframe']
candle_type = self._freqtrade.config.get('candle_type_def', CandleType.SPOT)
_data = {}
for pair in pairlist:
dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit)
_data[pair] = {
yield {
"key": (pair, timeframe, candle_type),
"df": dataframe,
"la": last_analyzed
}
return _data
def _ws_request_analyzed_df(self, limit: Optional[int]):
""" Historical Analyzed Dataframes for WebSocket """
whitelist = self._freqtrade.active_pair_whitelist

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@@ -1061,6 +1061,7 @@ class Telegram(RPCHandler):
try:
self._rpc._rpc_force_entry(pair, price, order_side=order_side)
except RPCException as e:
logger.exception("Forcebuy error!")
self._send_msg(str(e))
def _force_enter_inline(self, update: Update, _: CallbackContext) -> None: